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3.1 Introduction


This section provides an introduction to environmental statistics and data and covers the state of existing data and knowledge that contribute to any environmental assessment, including national-, regional- and global-level assessments. It attempts to elaborate the state of data collection and the use of data to compile statistics and produce indicators. Emerging areas of statistics, such as big data, citizen science and traditional knowledge – which are currently underutilized, but present tremendous opportunities for better measuring – are discussed in Chapter 25 of this report.


3.2 The demand for environmental statistics and data


Knowledge and data are essential bedrocks of environmental assessment. Without an evidence base to work from, conducting and publishing an accurate assessment is impossible. But what is an evidence base, and how do we generate it?


‘The Environment’ was traditionally considered to refer only to biophysical earth systems. But this paradigm is shifting. It is important not only to measure the state of the environment, but also to determine how environmental problems, which manifest in the biophysical environment, arise from social systems and economic arrangements, and how economic development and social well-being depend on the environment.


The GEO-5 report chapter on the Review of Data Needs presents the deficiencies in scientifically credible data on the environment; in particular, the report notes the need for time series on freshwater quantity and quality, groundwater depletion, ecosystem services, loss of natural habitat, land degradation, chemicals and waste, and other issues (United Nations Environment Programme [UNEP] 2012). It also acknowledges that the factual and scientific quality of an assessment rely on the quality and availability of data on the environment (UNEP 2012). Further, it indicates that more systematic data-collection can help governments, as well as regional and international bodies, to assess their progress towards international goals.


In his 2015 Millennium Development Goals (MDG) Report, Ban Ki Moon (Box 3.1) (United Nations 2015a) called for urgent and rapid improvements in data for the post-2015 agenda, especially its availability, reliability and timeliness. He urged governments to make substantial investments in their national statistics offices and systems, as well as to scale up the capacity and capability for producing high-quality data.


The Drivers, Pressures, State, Impact, Response (DPSIR) conceptual framework (see Section 1.6) is a useful framework for environmental monitoring and assessment. Many of the


Box 3.1: Statement from Ban Ki Moon, 2015


“Strong political commitment and significantly increased resources will be needed to meet the data demand for the new development agenda.”


Ban Ki Moon, 2015 (United Nations 2015)


drivers and pressures of environmental change are located in the social realm, and so are many of the impacts. Many environmental challenges are the result of inequalities in access to resources and institutions of power, as well as along the axes of gender, age, race, ethnicity, income and other social status.


As highlighted in the GEO-5 report (UNEP 2012), there is a need not only for regular monitoring data, but also for harmonization of data-collection approaches and methodologies. Governments rely on national statistical systems to provide the necessary data for national policy; however, historically, many national statistical systems have not considered environmental statistics to be within their purview.


3.3 History of environmental statistics


Historically, official statistics have risen in response to a clear demand from governments for information. The first Roman census was justified by the need for accountability in terms of taxation and military service (Hin 2007). National accounts were born out of the stock market crash of 1929 and the need for wartime statistics, which would allow countries to avoid economic catastrophe and provide information on how to pay for World War II (Stone 1947; Vanoli 2005). In 1947, the United Nations established the United Nations Statistical Commission (UNSC) to develop and promote statistical guidelines which could be used by countries for national monitoring. The scope of the Commission’s work covers statistical methodologies for keeping stock of the economy, and for policy on global macroeconomic stability, including economic growth, price movements and population dynamics, migration, mortality, births and longevity – but not the environment.


The Brundtland Commission of 1983 led to the Framework for the Development of Environment Statistics which was first adopted by the UN Statistical Commission in 1984. Later, the UNSC worked on environmental economic accounting which arose from the 1992 Earth Summit. There have been three revisions of the System of Environmental Economic Accounts (SEEA) these include the SEEA 1993, the SEEA 2003 and the SEEA 2012 – the latest was adopted as a statistical standard in 2012 (United Nations 1993; United Nations et al. 2003; United Nations 2012). Additionally, the Experimental Ecosystem Accounts were adopted in 2013. The link between these two statistical frameworks forms the basis for monitoring progress towards sustainable development and focuses on the effects of life on the environment and that of the environment on life.


There was a 91 per cent participation by countries and territories in the 2010 census round, and a 95 per cent submission rate of national accounts to the United Nations Statistics Division (United Nations 2015b; United Nations 2017a). However, for the first six decades of the UNSC, progress in official statistics was mostly related to demography and economic statistics. The adoption of the MDGs, which included goals focused mostly on social development, and the desire to track progress as measured by the MDG indicators was transformational in terms of increasing investment in statistics. The MDG implementation efforts resulted in increased statistical capacity of countries to produce and use statistics on poverty, education, health, gender, environment and governance (World Bank 2002; Organisation for Economic Co-operation and Development [OECD] 2015; United Nations 2016a).


The Current State of our Data and Knowledge 59 3


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